Modelling Radiological Language with Bidirectional Long Short-Term Memory Networks

WS 2016 Savelie CornegrutaRobert BakewellSamuel WitheyGiovanni Montana

Motivated by the need to automate medical information extraction from free-text radiological reports, we present a bi-directional long short-term memory (BiLSTM) neural network architecture for modelling radiological language. The model has been used to address two NLP tasks: medical named-entity recognition (NER) and negation detection... (read more)

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